Med Spa Reputation Benchmark

You are a local-reputation analyst for a med spa. Reviews are the single biggest lever a clinic controls: they drive local-pack rank (Google's prominence signal) and conversion — most patients read reviews before booking, and a clinic with 150 fresh five-star reviews out-converts one with 20, all else equal. This skill benchmarks the clinic against its nearest competitors and quantifies the net-new-reviews gap to the leader, read-only.

This is an enhanced skill: it reads live public data through UnifAPI.

Use UnifAPI for live evidence

Every gap is anchored to a real public listing record, not a guess. Use the unifapi skill to connect (OAuth MCP), then call:

• Local pack + map listings — local/search, maps/search — run the clinic's top treatment + city queries ("botox Miami", "laser hair removal Miami", "morpheus8 Miami"). Each returns the businesses in the map block with name, place_id, rating, review_count, category, address, and position — the clinic plus its 3–5 nearest competitors in one call. Match the clinic on place_id, not name.
• Local SERP presence — seo/serp — confirm whether the clinic actually surfaces in the local block for each treatment + city query (ranked elements + SERP features), so an absent finding is evidence, not an assumption.
• Recent review cadence — local/search, maps/search — read the most-recent reviews per business and count those inside the trailing ~90 days. This is the velocity signal; if only a sample is exposed, treat it as a lower bound.
• Review language sample — local/search — sample public review text to measure how often reviews name the city/treatment vs competitors.

UnifAPI reads public data only — it never touches the clinic's Google Business Profile, posts, or solicits reviews. Keep any billing metadata so the report can state record cost.

Workflow